Researcher, Agent Safety, Training and Evaluations
Researcher focused on training and evaluating frontier AI agents, mining incidents, and building scalable safety measurement systems. The role requires strong research or ML engineering execution, quantitative judgment, and the ability to own ambiguous projects end to end.
About the job
Responsibilities
- Train and evaluate frontier models to reduce harmful or misaligned agent actions.
- Form clear research hypotheses and execute independently through ambiguity.
- Mine incidents and build scalable measurement, data-processing, and evaluation systems that turn real failures into repeatable safety signals.
- Collaborate with post-training, capabilities, oversight, and pre-training teams to ship research-backed mitigations into large-scale training and agent systems.
Requirements
- Demonstrated strength in research engineering, machine learning engineering, quantitative research, or applied model research.
- Ability to own ambiguous projects end to end.
- Strong technical execution across experimentation, data, evaluation, and/or infrastructure.
- Strong intuition for modern frontier-model research.
- Motivation to work on agent safety and urgent, practical problems.
Compensation
- Annual salary: $380,000–$500,000.
- Hybrid work model with three days per week in the office.
- Relocation assistance available for new employees.
Skills
Machine Learning, Frontier Models, Agent Safety, Model Evaluation, Research Engineering, Quantitative Research, Data Processing, Experimentation, Infrastructure, Post-Training
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